The present invention relates to vascular disease detection and characterization in medical images, and more particularly, to vascular disease detection and characterization in medical images using recurrent neural networks.
Recent generations of computed tomography (CT) scanners enable the acquisition of high quality CT angiography (CTA) images, which can be used as an alternative to invasive angiography for ruling out vascular diseases such as coronary stenosis and plaque. This has led to the development of various algorithms for automated detection of vascular diseases in CTA images. However, due to the varying length of vascular branches, such algorithms typically rely on only local image features extracted along vascular branches, and hence are only able to produce local predictions that independently characterize centerline points along a vascular branch, but do not take into account an overall dependency between image features and predictions along the vascular branch.